Min-Max Scaling Form
Enter numbers separated by commas, spaces, semicolons, or line breaks. Leave source minimum and source maximum blank to detect them automatically.
Example Data Table
Example using source minimum 12, source maximum 36, target minimum 0, and target maximum 1.
| # | Original Value | Scaled Value |
|---|---|---|
| 1 | 12 | 0.00 |
| 2 | 18 | 0.25 |
| 3 | 24 | 0.50 |
| 4 | 30 | 0.75 |
| 5 | 36 | 1.00 |
Formula Used
Standard min-max scaling formula:
Scaled Value = ((x - Source Min) / (Source Max - Source Min)) × (Target Max - Target Min) + Target Min
Where: x is the original value being transformed.
This method maps each input value proportionally into a new target interval. It preserves order and relative spacing while changing scale. If manual source bounds are supplied, those values become the reference range. When clamping is enabled, values below the source minimum or above the source maximum are limited before scaling.
How to Use This Calculator
- Enter a dataset name for easier reporting and export labeling.
- Paste raw numeric values into the textarea using commas, spaces, or new lines.
- Leave source minimum and source maximum blank for automatic detection, or enter manual bounds for controlled scaling.
- Set your target minimum and target maximum, such as 0 to 1 or -1 to 1.
- Choose decimal precision and a chart style.
- Enable clamping if you want out-of-range values restricted to the chosen source bounds.
- Press Scale Dataset to see results above the form.
- Download the transformed table as CSV or PDF when needed.
Frequently Asked Questions
1. What does min-max scaling do?
Min-max scaling converts each value into a chosen target range, usually 0 to 1. It keeps the relative order of data points while changing their numeric scale for modeling, charting, and comparison tasks.
2. When should I use manual source bounds?
Use manual source bounds when you need consistent scaling across multiple datasets or future observations. This is common in machine learning pipelines where training and incoming data must follow the same transformation rules.
3. What happens if all source values are identical?
Scaling requires a nonzero source range. If the source minimum equals the source maximum, the formula would divide by zero. The calculator blocks that case and asks for a valid range.
4. Why would I enable clamping?
Clamping is useful when you want values outside the manual source range forced to the nearest bound. It prevents transformed results from extending below the target minimum or above the target maximum.
5. Does min-max scaling remove outliers?
No. It rescales numbers but does not remove extreme values. In fact, outliers can strongly affect the source minimum and source maximum, which changes how all other values are positioned.
6. Is min-max scaling better than z-score standardization?
Neither method is always better. Min-max scaling is ideal when fixed bounds matter. Z-score standardization is often better when distribution shape and distance from the mean are more important.
7. Can I scale values into a range other than 0 to 1?
Yes. You can enter any target minimum and target maximum, such as -1 to 1, 10 to 100, or other custom intervals. The same proportional formula still applies.
8. Why are CSV and PDF exports useful?
CSV export helps you reuse results in spreadsheets, notebooks, or pipelines. PDF export is useful for reports, documentation, and sharing a clean summary of transformed data with others.